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October 13
Visual Storytelling: 6 Tips for Creating Effective Data Visualization

Audiences are typically drawn to storytelling. And, stories with pictures and visuals tend to be easier to understand. In the words of Rudyard Kipling “If history were taught in the form of stories, it would never be forgotten”.

Data visualization or Business Intelligence dashboards are today’s form of storytelling. They are “stories” designed to help end users understand the business, gain deeper perspectives of performance and make quicker decisions. But what makes a dashboard effective? A dashboard with a lot of colorful charts, while pleasing to look at, is not useful if it is not functional and does not help the end users with their responsibilities.

6 Tips for Creating Effective Data Visualization with a Business Intelligence Dashboard:   
1. A dashboard should be designed for a certain user or user type. Unlike most software applications which have a common interface for its entire user base, a dashboard is unique for its intended audience. As such, it is key to understand the audience, their needs and requirements, and their roles within the organization. For example, let’s assume that you are creating a financial dashboard for a retail chain to analyze the performance of their stores. This would involve creating charts displaying data points such as income, expense and net profit. However, the level of data displayed depends on the person viewing the dashboard. For a CFO, the data would encompass all the stores, for a regional director it would only be stores within a particular region and for a district manager, it would only involve stores within a particular district. Additionally each user will have different needs and/or additional data points that would be applicable to their role. Hence, choosing the right data set and associated subsets of data is critical.

2. A dashboard should be laid out in a logical, interactive and simple to use progression by initially providing the user with an “at-glance” overview and then allowing the user to contextually explore the data by using tools such as drill downs, filters and alerts.
3. Select a visualization based on its functionality. For example,

  • Use a pie chart, stacked bar chart or a stacked area graph when displaying the composition of a measure.
  • Use a line graph to display trends.
  • Use a scatter chart to display distribution.
  • Use KPI indicators for comparison.
  • Choose a visualization that is easier for the user to understand. Remember that the visual display is a tool to convey information not raw data. If the user has to translate the data being presented into a form they understand, the choice of visual display has to be changed.

4.  A dashboard should have a visual impact without compromising its usability. This involves choosing the appropriate colors for displaying the data points. As such a few tips:

  • Choose a color based on the common understanding of the same. (Red means bad, Green means good).
  • Use the same color for the same data point to display relationships between different portions of the dashboard
  • Use shades of the same color when displaying progressions in a data point.
  • Choose colors to achieve maximum contrast between data points and distinguish them for any background and foreground elements of a dashboard.

5. Ensure that a dashboard fits within a screen without the need for scrolling. This ensures that the user is able to quickly and easily understand the information being displayed. This is because the human brain can process information faster and with ease when all related data elements are presented together.

6. Data without context is of no use. A well laid out and appropriate visualization with the right dash of colors is only as good as a paper weight if the use does not know what data points are being displayed. Providing context using tools such as data labels, report titles and tool tips will increase the dashboard’s readability and hence it usefulness.

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